Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

An integrated modelling approach to assess the risk of wind-borne spread of foot-and-mouth disease virus from infected premises

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock that has serious consequences on livestock production and trade. In Australia, preparedness and planning includes the development of decision-support tools that would assist priority setting and resource management in the event of an incursion. In this paper we describe an integrated modelling approach using geographic information system (GIS) technology to assess the risk of wind-borne spread of FMD virus. The approach involves linking an intra-farm virus production model, a wind transport and dispersal model, and an exposure-risk model to identify and rank farms at risk of wind-borne infection of FMD. This will assist authorities by enabling resources for activities like surveillance and vaccination to be allocated on the basis of risk.     

A pragmatic approach to study the groundwater quality suitability for domestic and agricultural usage,Saq aquifer,northwest of Saudi Arabia

The present study deals with detailed hydrochemical assessment of groundwater within the Saq aquifer. The Saq aquifer which extends through the NW part of Saudi Arabia is one of the major sources of groundwater supply. Groundwater samples were collected from about 295 groundwater wells and analyzed for various physico-chemical parameters such as electrical conductivity (EC), pH, temperature, total dissolved solids (TDS), Na⁺, K⁺, Ca²⁺, Mg²⁺, CO₃ ^?, HCO₃ ^?, Cl^?, SO₄ ^2?, and NO₃ ^?. Groundwater in the area is slightly alkaline and hard in nature. Electrical conductivity (EC) varies between 284 and 9,902?μS/cm with an average value of 1,599.4 μS/cm. The groundwater is highly mineralized with approximately 30 % of the samples having major ion concentrations above the WHO permissible limits. The NO₃ ^? concentration varies between 0.4 and 318.2 mg/l. The depth distribution of NO₃ ^? concentration shows higher concentration at shallow depths with a gradual decrease at deeper depths. As far as drinking water quality criteria are concerned, study shows that about 33 % of samples are unfit for use. A detailed assessment of groundwater quality in relation to agriculture use reveals that 21 % samples are unsuitable for irrigation. Using Piper’s classification, groundwater was classified into five different groups. Majority of the samples show Mix-Cl-SO₄- and Na-Cl-types water. The abundances of Ca²⁺ and Mg²⁺ over alkalis infer mixed type of groundwater facies and reverse exchange reactions. The groundwater has acquired unique chemical characteristics through prolonged rock-water interactions, percolation of irrigation return water, and reactions at vadose zone.     

Modified Grey Model and its application to groundwater flow analysis with limited hydrogeological data: a case study of the Nubian Sandstone, Kharga Oasis, Egypt

Groundwater flow at Kharga Oasis, located in the western desert of Egypt, was previously analyzed using numerical models; however, the lack of basic data often limits the implementation of these models, as well as introducing a problem for model calibration and validation. The Grey Model (GM) was used to overcome these difficulties of data limitation and uncertainty of hydrogeological conditions. However, no clear theories exist for selecting the number of input model trends and the most suitable values of input parameters. Therefore, in the current study, a modification of the GM is newly proposed and called the Modified Grey Model (MGM) in an attempt to determine a process for selecting the best input models' trends with the appropriate values of input parameters to achieve acceptable fitting to observations. The sensitivity analysis results showed that the MGM produced more stable results than the GM using a wide range of values for input parameters. Moreover, the MGM reduced the calculation time required for fitting the measured piezometric level trends by 99.8 %. Three development scenarios of groundwater withdrawal were proposed that involved either expanding the present extraction rate or redistributing the groundwater withdrawal over the recent working production wells (RWPWs). The results concluded that the groundwater table in the northern part of the oasis could be temporally recovered to an economical piezometric level; however, the table in the southern part is severely decreased. Therefore, new production wells are recommended to be constructed in the southern part far enough from the RWPWs.     

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin,northeastern China,from 2011 to 2015

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD₅) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.